Abstract
Recent studies point to power consumption becoming the major design constraint in exascale computing systems. Current scientific benchmarks, such as LINPACK, only evaluate high-performance computing (HPC) systems when running at full throttle, i.e., 100 % workload, resulting in more of a focus on performance than on power and energy consumption. In contrast, efforts like SPECpower evaluate the energy efficiency of a server at varying workloads. This is analogous to evaluating the fuel efficiency of an automobile at varying speeds. However, the applicability of SPECpower to HPC is limited at best.
Given the absence of a scientific benchmark to evaluate the energy efficiency of HPC system at different workloads, we propose GBench (short for Green Benchmark), a methodology to evaluate the energy efficiency of supercomputers and enable a more rigorous study of energy efficiency in HPC. We use LINPACK as a case study and demonstrate the efficacy of our methodology by identifying application parameters impacting performance and providing a systematic methodology to vary the workload of LINPACK.
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Notes
Exascale systems are predicted to consume about 67 megawatts (MW) of power [2].
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This project was supported in part by the US National Science Foundation (NSF) via grant CCF-0848670.
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Subramaniam, B., Feng, Wc. GBench: benchmarking methodology for evaluating the energy efficiency of supercomputers. Comput Sci Res Dev 28, 221–230 (2013). https://doi.org/10.1007/s00450-012-0218-0
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DOI: https://doi.org/10.1007/s00450-012-0218-0